Health Status Assessment

 

What is a health status assessment?

A health status assessment of a population establishes whether particular health problems exist in a given population, characterizes the problems and identifies the potential for avoidable mortality and morbidity. It can be used to support health needs assessment, for example, describe patterns of disease in a population and compare it other populations. It can also be used in policy making, aiding planning (e.g. resource allocation and target setting), evaluation and to identify areas for further research.

Steps in Health Status Assessment

1. Define the purpose of the assessment

2. Define the population (and any comparative population)

3. Define the aspects of health to be considered

4. Identify and review existing data sources

  • Are good local data available?
  • Are routine local or national statistics available?
  • Are relevant published surveys available?

5. Select the most appropriate existing data

  • Think C.A.R.T (i.e completeness, accuracy, relevance, timeliness) plus bias and generalisability

6. Make good use of the data

7. Consider if specific issues require specially collected data (should a special survey be undertaken?)

8. Communicate the results of the assessment

9. Evaluate the health status assessment

Note that use of simple workable definitions is important to health status assessments. Definitions should be 

  1. easy to use; 
  2. easy to measure in a standard manner; 
  3. easy to measure under a variety of settings; 
  4. can be used by different people 
  5. highly likely to produce the same result if used twice by the same person.

Some principles

  1. Crude numbers of affected individuals must be related to the number at risk, giving a rate
  2. All the data should be used wherever possible
  3. The source of a disease and methods of limiting it can be identified without necessarily knowing the cause
  4. Risk factors are characteristics or habits that are consistently more common in those who suffer from a disease than in those who do not


Useful Epidemiological Terms to Help Understanding of Health Status Assessments (and other studies)

Demography

The term demography is used to describe the study of populations on a national, regional or local basis. Changes in population are commonly measured by death rate, birth rate and life expectancy. Life span can be measured by death rates or life expectancy at a certain age. Infant mortality is often used as an indicator of the health status of a community. Assumption is it is sensitive to socioeconomic status of an area or country. Life expectancy is the average number of years we expect an individual of a give age to live if current mortality trends continue. There are different ways to measure this – e.g. life expectancy at birth, attaches greater importance to deaths in infancy than to deaths later in life. Life expectancy at later ages may be used to examine the impact of the environment or health services on older people.

Morbidity

Morbidity is the state of being diseased and its measurement is important in long term or disabling conditions. Morbidity can be classified as impairment, disability or handicap. Disabilities can have varying severity which will be affected by environmental factors (e.g. poor housing).

Incidence

Incidence measures the number of new episodes of illness arising in a population during a specified period. It can be measured as a rate:

Number of new cases of a disease in a specified period/No of person years at risk during period (i.e. average number at risk during period X length of period)

Sometimes measuring incidence is difficult because of changes in the population at risk during the time over which data was collected. This can be overcome by dividing the number of cases per year by the total number of person-years at risk. In this, we add the periods during which each member of the population is at risk. In this way, people who die or move away are no longer at risk and we can take them out of the calculation. The incidence rate should take into account the variable time periods individuals are disease free and at risk of developing the disease. Often it is not possible to measure disease-free periods precisely so we calculate it approximately by multiplying the average size of the study population by the length of the study period. (This is good if population is stable and incidence rate is low).

Prevalance

Prevalence of a disease is the number of people in a population that have the disease either at particular time (point prevalence) or over a stated period (period prevalence).

Period Prevalence = number of cases during a specified period/Total population at mid-point interval

Point prevalence = number of cases at a given time/Total population

Prevalance is often expressed as case per 100 population or 1000 population. Data regarding population at risk are often not available so total population in the study area is used as an approximation. Prevalence is lowered through death or cure (not treatment, e.g. diabetes and insulin). Prevalence studies are influenced by the chance of surviving with a disease and so do not give very strong evidence when we are trying to determine the cause of a disease.

Measuring incidence and prevalence involves counting cases in defined populations at risk. This alone can give an impression of the overall size of the problem. When diseases are short lived (either cured or fatal at early stage), prevalence is low compared to incidence. Disease with a low mortality and low cure rate are the opposite. Diseases that are common have a higher incidence and prevalence rates than those which are rare. When prevalence is low (and only then), Prevalence = incidence X duration.

Advantages and Disadvantages of Prevalance

Advantages are: 

  1. Measures of prevalence are helpful for deciding the need for health care and the planning of health services. High rates can suggest those areas that, because of the nature of the population or the environment, are generating more cases. 
  2.  Prevalence rates can be used to measure the occurrence of conditions where the onset of disease may be gradual – e.g. Maturity onset diabetes. (low incidence but are long term).

Disadvantages can involve calculations with the numerator 

  1. Who has the disease? (Depends on diagnostic system) 
  2. How to find the cases? (Regular data/surveillance; special survey; problems with hospital data).

It can also involve calculations of the demoninator: 

  1. Selective undercounting of certain groups (e.g. young ethnic people) 
  2. Does everyone in population have chance to be diseased?

Often routine data on incidence and prevalence are not available, hospital data are used. For examle, hospital admission of people with fractured neck of femur is one disease where hospital data closely resemble the true incidence (majority would be admitted). Prevalence of schizophrenia can be calculated from hospital data because severity and specialist nature of the treatment required for the disease means that virtually all cases are admitted at least once during a 5 year period.

Rates

The bottom figure of a rate is the denominator and the number on top is the numerator. For example: infant mortality in UK, the numerator would be deaths in infants aged 1 year and under and the denominator would be live births during the year and rate is 5.1 infant deaths per 1000 live births. Population at risk is the proportion of the population that is susceptible to a disease.

Cumulative incidence rate

Cumulative incidence rate of a specific disease depends on both the incidence rate and the length of the period of interest. Incidence rate usually changes with age, so age-specific incidence rates must also be considered. Cumulative incidence is a useful approximation when the incidence rate is low or when the study period is short. New cases are collected over a period and these are simply added to the total over that period. It is used where the disease in question is chronic or at least, continues over the collection period. E.g. dementia – 4% for people over 65 years. A form of cumulative incidence rate is case fatality rate which is the number of people who die from a disease/number of people with the disease.

Crude Rates

Estimations (incidence, prevalence or mortality rates) are known as crude values if they refer to the population as a whole. Crude mortality rate = number of deaths in a specified period/Average total population during that period X 1000. However, crude rates take no account of the fact that the chance of dying varies according to age, sex, race, socioeconomic class and other factors. It is usually not appropriate to use crude death rates for comparing different time periods or different geographic areas.

Age Specific Rates

Specific rates are used commonly to examine data for different groups, usually made on the basis of age, sex or social class. Age specific death rate = number of deaths in each age or sex group in a period/average number of people in age or sex population in the period.

Standardised Rates

Standardised rates or adjusted rates are a way of summarising the specific rates for 2 or more populations. The specific rates in each population are used as if the subgroups (e.g. age groups) were the same (standardised) for both populations. This is useful for describing the underlying difference in populations whilst controlling for their known attributes. The use of standardised rates allows a direct comparison to be made of the impact of a disease on mortality in different areas with different population structures. By using age-standardised rates, we can eliminate the influence of different age distributions on the mortality rates. We need to take into account the age distribution of different populations before directly comparing their death rates, this is because of the close relationship between mortality and age.

Standardised Mortality Ratio

Standardised Mortality Ratio (SMR) corrects for the distribution of the population by age and sex and produces an index that enables one to compare the mortality occurring in two different populations. It is an indicator which tells us whether the mortality rate among a particular subgroup or area is above or below the average for the whole population. If SMR = 100, it's the same as the population average. Less than 100, the mortality rate is below.